SIGN UP WALLET A BLOCK CHAIN BASED PERSONALLY IDENTIFIABLE INFORMATION (PII) MASKING USING LOOKUP SUBSTITUTION
Authors/Creators
Description
Digital identity is akin to a digital version of a physical ID, such as a passport or driver’s license, containing
various attributes that represent a user online. Currently, centralized and federated identity management systems,
such as those enabling logins via Google or Facebook, dominate the digital landscape. While these systems
simplify access, they pose significant risks. Centralized systems are vulnerable to large-scale data breaches, and
federated models often allow companies to track user data without consent. Existing identity management
approaches either rely on centralized servers or entrust identity providers with user authentication, often
compromising data privacy and hindering the portability of identity information. To address these challenges, a
more secure and reliable system is necessary—one that empowers users to manage their digital identities
independently and securely. This need has driven the development of the Sign Up Wallet, a Self-Sovereign
Identity (SSI) model utilizing blockchain and machine learning to safeguard digital identities. Blockchain
technology supports decentralized identity management, removing the need for third-party identity providers,
while machine learning identifies trusted service providers. Users store their digital identity within the Sign Up
Wallet using cryptographic keys. When interacting with a service provider, they submit a Unique Personal
Identifier (UPI) for direct credential verification. To assess the trustworthiness of websites, Logistic Regression
is employed. If a service provider is deemed untrustworthy, a masked credential is generated using a Lookup
Substitution Algorithm, ensuring privacy during the verification process. This approach allows for secure
verification without exposing sensitive data, granting individuals greater control over their digital identities and
reducing reliance on centralized authorities, thus minimizing the risks of data breaches and privacy
infringements.
Files
Aug-2024-11-1723394871-AUG10.pdf
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(708.1 kB)
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Additional details
Dates
- Accepted
-
2024-08-12